Title :
Statistical optimisation and tuning of GA factors
Author :
Petrovski, Andrei ; Brownlee, Alexander ; McCall, John
Author_Institution :
Sch. of Comput., Robert Gordon Univ., Aberdeen
Abstract :
This paper presents a practical methodology of improving the efficiency of genetic algorithms through tuning the factors significantly affecting GA performance. This methodology is based on the methods of statistical inference and has been successfully applied to both binary-and integer-encoded genetic algorithms that search for good chemotherapeutic schedules
Keywords :
cancer; drugs; genetic algorithms; inference mechanisms; patient treatment; statistical analysis; GA factors; binary-and integer-encoded; chemotherapeutic schedules; genetic algorithm; statistical inference; statistical optimization; Algorithm design and analysis; Analysis of variance; Application software; Computer science; Encoding; Genetic algorithms; Genetic engineering; Performance analysis; Processor scheduling; Space exploration;
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Conference_Location :
Edinburgh, Scotland
Print_ISBN :
0-7803-9363-5
DOI :
10.1109/CEC.2005.1554759
